Who is it working for? The messy realities of AI in practice.
About this episode
The episode discusses the complexities of AI tools in real-world applications and their impact on various stakeholders.
What happens when your brand new tool makes things worse for low performing entrepreneurs? Or restricts your most successful teachers so they can't unlock the full power of their skills? One of the most important questions you can ask about an AI tool is NOT, "is it working?" You really need to ask, "who is it working for?" and "How did the change happen?" Crystal Huang from IDinsight and Matthew Smith from IDRC talk about ways to evaluate AI tools, and how to think about if they really are creating the change you hoped for. Just like the internet didn't end poverty, neither will AI. What succeeds or fails will depend on how well we implement AI, and whether we can truly center how technology connects to humans and real life contexts. What do we do to take something that works in a controlled setting and help it survive the messiness of real-world implementation?
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